I already read the document and it is pretty good. Unfortunately, in the real world there are still complex scenarios that cannot be optimized with the techniques used here. I hope that in future versions the SSAS engine will provide some more advanced optimizations for similar cases. One of the first step could be simply automating the optimizations made “by hand” like the Matrix Relationship Optimization shown in the paper. Another would be the simplification for defining efficient aggregations when many-to-many relationships are involved (now you could create a lot of aggregations that are unused when M2M are involved, and sometimes users query a cube only using M2M relationships – you have to tune the aggregations manually).

This article describes how DAX automatically converts data types in arithmetic operations. These small details can cause and explain differences in results when using the same operations in other languages. Read more

This article describes how to use the detail rows expression of a measure to obtain the equivalent of creating table functions in DAX. This allows the reusing of a table expression in multiple CALCULATE filters. Read more